灵巧家庭爬行器：半自动IoT传感器集成框架
Smart Home Crawler: Towards a framework for semi-automatic IoT sensor integration
摘要：
灵巧家庭中的传感器部署长期以来一直与家庭自动化、家庭安全或能源消耗意识和减少等应用具有商业相关性。然而，由于传感器设备和网关的异构性，数据集成仍然是一个昂贵且耗时的过程。在本文中，我们提出了灵巧家庭爬虫框架，（1）提供了一个共同的语义抽象的底层传感器和网关技术，（2）加速新设备的集成，通过应用机器学习技术，发现的设备连接到一个语义数据模型。我们展示了在ICT 2018上展示的第一个原型。该原型是作为物联网安全和隐私保护搜索引擎IoTCrawler的特定于域的爬行组件构建的。
英文摘要：
Sensor deployments in Smart Homes have long reached commercial relevance for applications such as home automation, home safety or energy consumption awareness and reduction. Nevertheless, due to the heterogeneity of sensor devices and gateways, data integration is still a costly and timeconsuming process. In this paper we propose the Smart Home Crawler Framework that (1) provides a common semantic abstraction from the underlying sensor and gateway technologies, and (2) accelerates the integration of new devices by applying machine learning techniques for linking discovered devices to a semantic data model. We present a first prototype that was demonstrated at ICT 2018. The prototype was built as a domainspecific crawling component for IoTCrawler, a secure and privacy-preserving search engine for the Internet of Things.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
